Capture session learnings and propose skill improvements from conversation history.
npx skills add https://github.com/lzlatkin/dots --skill improve-lzlatkin
Please help me install this Agent Skill. Skill: improve Source: https://github.com/lzlatkin/dots/tree/main/agents/skills/improve Command: npx skills add https://github.com/lzlatkin/dots --skill improve-lzlatkin
This Skill streamlines the process of capturing learnings from AI sessions, improving existing skills, and updating the knowledge base to make future AI interactions more effective.
/improve to automatically document the solution, update the relevant skill to handle similar issues in the future, and capture the root cause in the project's knowledge base.Run /improve at the end of any session to capture learnings and suggest skill improvements.
High-intent search queries and answers about installing and using this skill.
To capture session learnings for AI agent capabilities, run a post-session analysis command to automatically extract durable knowledge from conversation history and add it to a structured knowledge base. This automates continuous improvement of your AI workflows.
The best way to identify codebase gaps like missing documentation is to run a post-session analysis on your conversation history and codebase context. This detects missing tests or configuration and suggests actionable fixes automatically.
Automated skill refinement works by analyzing session interactions against existing skill definitions to identify weaknesses. It then proposes actionable changes to existing AI skills to handle similar issues more effectively in the future.
Yes, you can use post-session analysis for continuous knowledge management without manual entry. The process analyzes conversation history and automatically extracts durable knowledge to update your project's structured knowledge base.
Yes, providing conversation history and codebase context is required for automated knowledge capture. The tool requires these inputs to accurately analyze session interactions and propose actionable changes to skills and documentation.
You should run continuous improvement commands at the end of any complex AI session. This ensures that debugging solutions, root causes, and codebase gap fixes are automatically documented and applied to future agent capabilities.
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